class_docstr: DreamerV3 specific Learner class.
  
  Only implements the `additional_update_for_module()` method to define the logic
  for updating the critic EMA-copy after each training step.
docstr: Updates the EMA weights of the critic network.
docstr_tok: ["Updates","the","EMA","weights","of","the","critic","network","."]
code: def additional_update_for_module(
      self,
      *,
      module_id: ModuleID,
      config: DreamerV3Config,
      timestep: int,
  ) -> Dict[str, Any]:
      """Updates the EMA weights of the critic network."""
  
      # Call the base class' method.
      results = super().additional_update_for_module(
          module_id=module_id, config=config, timestep=timestep
      )
  
      # Update EMA weights of the critic.
      self.module[module_id].critic.update_ema()
  
      return results
  
file_path: ray/python/ray/rllib/algorithms/dreamerv3/dreamerv3_learner.py
imports: from typing import Any, DefaultDict, Dict
  from ray.rllib.algorithms.dreamerv3.dreamerv3 import DreamerV3Config
  from ray.rllib.core.learner.learner import Learner
  from ray.rllib.policy.sample_batch import MultiAgentBatch
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.typing import ModuleID, TensorType
label_desc: Use image node_id 2 for calling the DreamerV3Learner obj's underlying member method code with example usage: obj.additional_update_for_module() and returns: results